Wearable, mobile and/or portable computer terminals or devices are used for a wide variety of tasks. Such terminal devices allow the workers using them (“users”) to maintain mobility, while providing the users with desirable computing and data gathering and processing functions. Furthermore, such mobile terminal devices often provide a communication link to a larger, more centralized management computer and/or computer system that directs the activities of the user and processes any collected data. Often, such mobile terminal devices are implemented in speech-directed or speech-assisted work environments. In such environments, a speech dialog is maintained between the terminal device and a user. The terminal devices include a speech engine that is implemented in processor hardware and software and the terminal devices connect with a headset for the purpose of maintaining a speech dialog with a user. The speech engine includes a speech recognition function that recognizes speech that is captured from a user through the headset and also includes a text-to-speech (TTS) function that converts data to speech to be played to the user through the headset. In that way, a speech dialog is maintained between the terminal device and the user for facilitating various work tasks. In addition to the speech dialog, various peripheral devices might be implemented and interfaced with the terminal device, such as barcode or RFID readers, displays, printers, or other devices to operate in conjunction with the speech dialog for facilitating the various work tasks.
One example of a specific use for a wearable/mobile/portable terminal device is a within a product management system that involves product distribution and tracking as well as product inventory management. Such systems are sometimes referred to as warehouse management systems (WMS). In a conventional WMS system, a large number of users (each using a terminal device) are directed, through speech, to move around throughout a warehouse and complete various tasks, such as to pick certain products to fill an order or to put away or replenish items at storage locations. To that end, the terminal devices are loaded prior to the start of each user work shift with one or more work applications. The work applications are then executed by the user and such work applications usually include a plurality of tasks that are to be performed by the user. Using a speech dialog through a terminal device and headset, a user is directed to move around to various locations, to perform various tasks and to respond to inquiries using speech. In that way, the various tasks are completed and data that is associated with the work application is gathered. The terminal devices incorporate wireless radios (e.g. WiFi radios) or other communication links in order to exchange data with servers running the WMS system for the purposes of managing the workflow. The terminal devices also communicate with one or more management applications for the purposes of managing and configuring the terminal devices, loading work applications onto the terminal devices, managing the users that are working with the terminal devices, and providing system diagnostics.
Such mobile terminal devices utilize portable power elements, such as batteries to power their electronics. For efficient use of such terminal devices during a work shift, it is desirable to monitor and manage the battery life of each device so that the user knows when they may need to replace or recharge the batteries of their device. Currently, warehouse management systems and terminal management systems can only provide a somewhat coarse, and not particularly accurate, indication to a user of the existing battery life for the battery in their device. Certain power management schemes in such systems generally rely only upon battery operating parameters for a single device. For example, a management scheme may monitor battery life based upon the measured output voltage of the battery or may monitor some other battery operational metric. However, such power management schemes do not take into account the particular features of the use of the battery or a specific workflow. Nor do such schemes go beyond the individual device or look at groups of user devices and batteries that might have common usage characteristics. However, such a voltage parameter or other operational metric, in most cases, is not a sufficient or accurate measurement for determining remaining battery life. This is because the battery operational parameters or metrics like voltage will not be particularly linear parameters. Furthermore, the run-time remaining for a particular battery is affected by many factors, such as the actual power consumption profile of the particular device.
The power consumption of a device may vary somewhat radically based upon the various voice applications that are in use. For example, the load of the CPU or other processor required by a work application is different between various work applications. Furthermore, the network traffic that is maintained by the terminal, such as to communicate with the WMS system may vary significantly between terminals. Still further, different peripheral devices used with the terminal device can drastically change how much power the terminal device is consuming. Therefore, it is difficult to accurately measure power consumption at different times within a work shift. Still further, the power consumption of the different work applications being run on a device may also vary, wherein some applications consume power in bursting spikes of high power consumption, while other work applications might consume a higher consistent and average amount of power. All these factors affect how accurately battery life may be predicted. Since changing batteries, or losing power within the middle of a particular work application or shift cuts down on the efficiency of a user, and therefore, increases the overall cost of the process, it is desirable to provide indications of battery life and power consumption that are more accurate than those that currently exist.
Accordingly, there is a need, unmet by current communication systems and mobile devices, to address the issues noted above. There is particularly an unmet need in the area of increasing efficiency and accuracy in managing the power consumption of mobile devices.